Yeast genetic interaction screens in the age of CRISPR/Cas

Simplicity within biological complexity

Motivation

Heterogeneous, interconnected, systems-level, molecular (multi-omic) data have become increasingly available and key in precision medicine. We need to utilize them to better stratify patients into risk groups, discover new biomarkers and targets, repurpose known and discover new drugs to personalize medical treatment. Existing methodologies are limited and a paradigm shift is needed to achieve quantitative and qualitative breakthroughs.

Results

In this perspective paper, we survey the literature and argue for the development of a comprehensive, general framework for embedding of multi-scale molecular network data that would enable their explainable exploitation in precision medicine in linear time. Network embedding methods (also called graph representation learning) map nodes to points in low-dimensional space, so that proximity in the learned space reflects the network's topology-function relationships. They have recently achieved unprecedented performance on hard problems of utilizing few omic data in various biomedical applications. However, research thus far has been limited to special variants of the problems and data, with the performance depending on the underlying topology-function network biology hypotheses, the biomedical applications, and evaluation metrics. The availability of multi-omic data, modern graph embedding paradigms and compute power call for a creation and training of efficient, explainable and controllable models, having no potentially dangerous, unexpected behaviour, that make a qualitative breakthrough. We propose to develop a general, comprehensive embedding framework for multi-omic network data, from models to efficient and scalable software implementation, and to apply it to biomedical informatics, focusing on precision medicine and personalized drug discovery. It will lead to a paradigm shift in the computational and biomedical understanding of data and diseases that will open up ways to solve some of the major bottlenecks in precision medicine and other domains.

Combining Oligo Pools and Golden Gate Cloning to Create Protein Variant Libraries or Guide RNA Libraries for CRISPR Applications

Oligo pools are array-synthesized, user-defined mixtures of single-stranded oligonucleotides that can be used as a source of synthetic DNA for library cloning. While currently offering the most affordable source of synthetic DNA, oligo pools also come with limitations such as a maximum synthesis length (approximately 350 bases), a higher error rate compared to alternative synthesis methods, and the presence of truncated molecules in the pool due to incomplete synthesis. Here, we provide users with a comprehensive protocol that details how oligo pools can be used in combination with Golden Gate cloning to create user-defined protein mutant libraries, as well as single-guide RNA libraries for CRISPR applications. Our methods are optimized to work within the Yeast Toolkit Golden Gate scheme, but are in principle compatible with any other Golden Gate-based modular cloning toolkit and extendable to other restriction enzyme-based cloning methods beyond Golden Gate. Our methods yield high-quality, affordable, in-house variant libraries.

Optimized genome-wide CRISPR screening enables rapid engineering of growth-based phenotypes in Yarrowia lipolytica

CRISPR-Cas9 functional genomic screens uncover gene targets linked to various phenotypes for metabolic engineering with remarkable efficiency. However, these genome-wide screens face a number of design challenges, including variable guide RNA activity, ensuring sufficient genome coverage, and maintaining high transformation efficiencies to ensure full library representation. These challenges are prevalent in non-conventional yeast, many of which exhibit traits that are well suited to metabolic engineering and bioprocessing. To address these hurdles in the oleaginous yeast Yarrowia lipolytica, we designed a compact, high-activity genome-wide sgRNA library. The library was designed using DeepGuide, an sgRNA activity prediction algorithm and a large dataset of ∼50,000 sgRNAs with known activity. Three guides per gene enables redundant targeting of 98.8% of genes in the genome in a library of 23,900 sgRNAs. We deployed the optimized library to uncover genes essential to the tolerance of acetate, a promising alternative carbon source, and various hydrocarbons present in many waste streams. Our screens yielded several gene knockouts that improve acetate tolerance on their own and as double knockouts in media containing acetate as the sole carbon source. Analysis of the hydrocarbon screens revealed genes related to fatty acid and alkane metabolism in Y. lipolytica. The optimized CRISPR gRNA library and its successful use in Y. lipolytica led to the discovery of alternative carbon source-related genes and provides a workflow for creating high-activity, compact genome-wide libraries for strain engineering.

CRI-SPA: a high-throughput method for systematic genetic editing of yeast libraries

Biological functions are orchestrated by intricate networks of interacting genetic elements. Predicting the interaction landscape remains a challenge for systems biology and new research tools allowing simple and rapid mapping of sequence to function are desirable. Here, we describe CRI-SPA, a method allowing the transfer of chromosomal genetic features from a CRI-SPA Donor strain to arrayed strains in large libraries of Saccharomyces cerevisiae. CRI-SPA is based on mating, CRISPR-Cas9-induced gene conversion, and Selective Ploidy Ablation. CRI-SPA can be massively parallelized with automation and can be executed within a week. We demonstrate the power of CRI-SPA by transferring four genes that enable betaxanthin production into each strain of the yeast knockout collection (≈4800 strains). Using this setup, we show that CRI-SPA is highly efficient and reproducible, and even allows marker-free transfer of genetic features. Moreover, we validate a set of CRI-SPA hits by showing that their phenotypes correlate strongly with the phenotypes of the corresponding mutant strains recreated by reverse genetic engineering. Hence, our results provide a genome-wide overview of the genetic requirements for betaxanthin production. We envision that the simplicity, speed, and reliability offered by CRI-SPA will make it a versatile tool to forward systems-level understanding of biological processes.

A DNA assembly toolkit to unlock the CRISPR/Cas9 potential for metabolic engineering

CRISPR/Cas9-based technologies are revolutionising the way we engineer microbial cells. One of the key advantages of CRISPR in strain design is that it enables chromosomal integration of marker-free DNA, eliminating laborious and often inefficient marker recovery procedures. Despite the benefits, assembling CRISPR/Cas9 editing systems is still not a straightforward process, which may prevent its use and applications. In this work, we have identified some of the main limitations of current Cas9 toolkits and designed improvements with the goal of making CRISPR technologies easier to access and implement. These include 1) A system to quickly switch between marker-free and marker-based integration constructs using both a Cre-expressing and standard Escherichia coli strains, 2) the ability to redirect multigene integration cassettes into alternative genomic loci via Golden Gate-based exchange of homology arms, 3) a rapid, simple in-vivo method to assembly guide RNA sequences via recombineering between Cas9-helper plasmids and single oligonucleotides. We combine these methodologies with well-established technologies into a comprehensive toolkit for efficient metabolic engineering using CRISPR/Cas9. As a proof of concept, we developed the YaliCraft toolkit for Yarrowia lipolytica, which is composed of a basic set of 147 plasmids and 7 modules with different purposes. We used the toolkit to generate and characterize a library of 137 promoters and to build a de novo strain synthetizing 373.8 mg/L homogentisic acid.

Improving therapeutic protein secretion in the probiotic yeast Saccharomyces boulardii using a multifactorial engineering approach

The probiotic yeast Saccharomyces boulardii (Sb) is a promising chassis to deliver therapeutic proteins to the gut due to Sb's innate therapeutic properties, resistance to phage and antibiotics, and high protein secretion capacity. To maintain therapeutic efficacy in the context of challenges such as washout, low rates of diffusion, weak target binding, and/or high rates of proteolysis, it is desirable to engineer Sb strains with enhanced levels of protein secretion. In this work, we explored genetic modifications in both cis- (i.e. to the expression cassette of the secreted protein) and trans- (i.e. to the Sb genome) that enhance Sb's ability to secrete proteins, taking a Clostridioides difficile Toxin A neutralizing peptide (NPA) as our model therapeutic. First, by modulating the copy number of the NPA expression cassette, we found NPA concentrations in the supernatant could be varied by sixfold (76-458 mg/L) in microbioreactor fermentations. In the context of high NPA copy number, we found a previously-developed collection of native and synthetic secretion signals could further tune NPA secretion between 121 and 463 mg/L. Then, guided by prior knowledge of S. cerevisiae's secretion mechanisms, we generated a library of homozygous single gene deletion strains, the most productive of which achieved 2297 mg/L secretory production of NPA. We then expanded on this library by performing combinatorial gene deletions, supplemented by proteomics experiments. We ultimately constructed a quadruple protease-deficient Sb strain that produces 5045 mg/L secretory NPA, an improvement of > tenfold over wild-type Sb. Overall, this work systematically explores a broad collection of engineering strategies to improve protein secretion in Sb and highlights the ability of proteomics to highlight under-explored mediators of this process. In doing so, we created a set of probiotic strains that are capable of delivering a wide range of protein titers and therefore furthers the ability of Sb to deliver therapeutics to the gut and other settings to which it is adapted.

A DNA assembly toolkit to unlock the CRISPR/Cas9 potential for metabolic engineering

CRISPR/Cas9-based technologies are revolutionising the way we engineer microbial cells. One of the key advantages of CRISPR in strain design is that it enables chromosomal integration of marker-free DNA, eliminating laborious and often inefficient marker recovery procedures. Despite the benefits, assembling CRISPR/Cas9 editing systems is still not a straightforward process, which may prevent its use and applications. In this work, we have identified some of the main limitations of current Cas9 toolkits and designed improvements with the goal of making CRISPR technologies easier to access and implement. These include 1) A system to quickly switch between marker-free and marker-based integration constructs using both a Cre-expressing and standard Escherichia coli strains, 2) the ability to redirect multigene integration cassettes into alternative genomic loci via Golden Gate-based exchange of homology arms, 3) a rapid, simple in-vivo method to assembly guide RNA sequences via recombineering between Cas9-helper plasmids and single oligonucleotides. We combine these methodologies with well-established technologies into a comprehensive toolkit for efficient metabolic engineering using CRISPR/Cas9. As a proof of concept, we generated and characterized a library of 137 promoters and built a de novo Yarrowia lipolytica strain synthetizing 373.8 mg/L homogentisic acid.

Synthetic lethal gene pairs: Experimental approaches and predictive models

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

High throughput analysis of vacuolar acidification

Eukaryotic cells are compartmentalized into membrane-bound organelles, allowing each organelle to maintain the specialized conditions needed for their specific functions. One of the features that change between organelles is lumenal pH. In the endocytic and secretory pathways, lumenal pH is controlled by isoforms and concentration of the vacuolar-type H⁺-ATPase (V-ATPase). In the endolysosomal pathway, copies of complete V-ATPase complexes accumulate as membranes mature from early endosomes to late endosomes and lysosomes. Thus, each compartment becomes more acidic as maturation proceeds. Lysosome acidification is essential for the breakdown of macromolecules delivered from endosomes as well as cargo from different autophagic pathways, and dysregulation of this process is linked to various diseases. Thus, it is important to understand the regulation of the V-ATPase. Here we describe a high-throughput method for screening inhibitors/activators of V-ATPase activity using Acridine Orange (AO) as a fluorescent reporter for acidified yeast vacuolar lysosomes. Through this method, the acidification of purified vacuoles can be measured in real-time in half-volume 96-well plates or a larger 384-well format. This not only reduces the cost of expensive low abundance reagents, but it drastically reduces the time needed to measure individual conditions in large volume cuvettes.

Bridging Glycomics and Genomics: New Uses of Functional Genetics in the Study of Cellular Glycosylation

All living cells are coated with a diverse collection of carbohydrate molecules called glycans. Glycans are key regulators of cell behavior and important therapeutic targets for human disease. Unlike proteins, glycans are not directly templated by discrete genes. Instead, they are produced through multi-gene pathways that generate a heterogenous array of glycoprotein and glycolipid antigens on the cell surface. This genetic complexity has sometimes made it challenging to understand how glycosylation is regulated and how it becomes altered in disease. Recent years, however, have seen the emergence of powerful new functional genomics technologies that allow high-throughput characterization of genetically complex cellular phenotypes. In this review, we discuss how these techniques are now being applied to achieve a deeper understanding of glyco-genomic regulation. We highlight specifically how methods like ChIP-seq, RNA-seq, CRISPR genomic screening and scRNA-seq are being used to map the genomic basis for various cell-surface glycosylation states in normal and diseased cell types. We also offer a perspective on how emerging functional genomics technologies are likely to create further opportunities for studying cellular glycobiology in the future. Taken together, we hope this review serves as a primer to recent developments at the glycomics-genomics interface.

CRISPR-Based Genetic Manipulation of Candida Species: Historical Perspectives and Current Approaches

The Candida genus encompasses a diverse group of ascomycete fungi that have captured the attention of the scientific community, due to both their role in pathogenesis and emerging applications in biotechnology; the development of gene editing tools such as CRISPR, to analyze fungal genetics and perform functional genomic studies in these organisms, is essential to fully understand and exploit this genus, to further advance antifungal drug discovery and industrial value. However, genetic manipulation of Candida species has been met with several distinctive barriers to progress, such as unconventional codon usage in some species, as well as the absence of a complete sexual cycle in its diploid members. Despite these challenges, the last few decades have witnessed an expansion of the Candida genetic toolbox, allowing for diverse genome editing applications that range from introducing a single point mutation to generating large-scale mutant libraries for functional genomic studies. Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technology is among the most recent of these advancements, bringing unparalleled versatility and precision to genetic manipulation of Candida species. Since its initial applications in Candida albicans, CRISPR-Cas9 platforms are rapidly evolving to permit efficient gene editing in other members of the genus. The technology has proven useful in elucidating the pathogenesis and host-pathogen interactions of medically relevant Candida species, and has led to novel insights on antifungal drug susceptibility and resistance, as well as innovative treatment strategies. CRISPR-Cas9 tools have also been exploited to uncover potential applications of Candida species in industrial contexts. This review is intended to provide a historical overview of genetic approaches used to study the Candida genus and to discuss the state of the art of CRISPR-based genetic manipulation of Candida species, highlighting its contributions to deciphering the biology of this genus, as well as providing perspectives for the future of Candida genetics.

Multigene editing: current approaches and beyond

CRISPR/Cas9 multigene editing is an active and widely studied topic in the fields of biomedicine and biology. It involves a simultaneous participation of multiple single-guide RNAs (sgRNAs) to edit multiple target genes in a way that each gene is edited by one of these sgRNAs. There are possibly numerous sgRNA candidates capable of on-target editing on each of these genes with various efficiencies. Meanwhile, each of these sgRNA candidates may cause unwanted off-target editing at many other genes. Therefore, selection optimization of these multiple sgRNAs is demanded so as to minimize the number of sgRNAs and thus reduce the collective negative effects caused by the off-target editing. This survey reviews wet-laboratory approaches to the implementation of multigene editing and their needs of computational tools for better design. We found that though off-target editing is unavoidable during the gene editing, those disfavored cuttings by some target genes' sgRNAs can potentially become on-target editing sites for some other genes of interests. This off-to-on role conversion is beneficial to optimize the sgRNA selection in multigene editing. We present a preference cutting score to assess those beneficial off-target cutting sites, which have a few mismatches with their host genes' on-target editing sites. These potential sgRNAs can be prioritized for recommendation via ranking their on-target average cutting efficiency, the total off-target site number and their average preference cutting score. We also present case studies on cancer-associated genes to demonstrate tremendous usefulness of the new method.

Genetic interaction analysis in microbial pathogens: unravelling networks of pathogenesis, antimicrobial susceptibility and host interactions

Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host-pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host-pathogen interactions. .

The yeast platform engineered for synthetic gRNA-landing pads enables multiple gene integrations by a single gRNA/Cas9 system

Saccharomyces cerevisiae is a versatile microbial platform to build synthetic metabolic pathways for production of diverse chemicals. To expedite the construction of complex metabolic pathways by multiplex CRISPR-Cas9 genome-edit, eight desirable intergenic loci, located adjacent to highly expressed genes selected from top 100 expressers, were identified and fully characterized for three criteria after integrating green fluorescent protein (GFP) gene - CRISPR-mediated GFP integration efficiency, expression competency assessed by levels of GFP fluorescence, and assessing growth rates of GFP integrated strains. Five best performing intergenic loci were selected to build a multiplex CRISPR platform, and a synthetic 23-bp DNA comprised of 20-bp synthetic DNA with a protospacer adjacent motif (PAM) was integrated into the five loci using CRISPR-Cas9 in a sequential manner. This process resulted in five different yeast strains harbouring 1-5 synthetic gRNA-binding sites in their genomes. Using these pre-engineered yeast strains, simultaneous integrations of 2-, 3-, 4-, or 5-genes to the targeted loci were demonstrated with efficiencies from 85% to 98% using beet pigment betalain (3-gene pathway), hygromycin and geneticin resistance markers. Integrations of the multiple, foreign genes in the targeted loci with 100% precision were validated by genotyping. Finally, we further developed the strain to have 6th synthetic gRNA-binding site, and the resulting yeast strain was used to generate a yeast strain producing a sesquiterpene lactone, kauniolide by simultaneous 6-gene integrations. This study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in yeast.

Systematic High-Content Screening of Fluorescently Tagged Yeast Double Mutant Strains

We describe a protocol for high-content screening in budding yeast that can be used to study genetic interactions from a cell biological perspective. This approach can be used to map genetic interactions by monitoring one or more subcellular fluorescent markers of interest. In this case, changes in the morphology or abundance of a subcellular compartment, pathway or bioprocess are monitored in the background of a systematic array of yeast double mutants. Alternatively, the protocol can be used to monitor proteome-wide abundance and localization changes in a double mutant of interest by screening the yeast ORF-GFP collection. The protocol can be readily adapted for high-content screening of triple mutants, other large-scale yeast collections or expanded to screening of multiple growth conditions.

A self-consistent probabilistic formulation for inference of interactions

Large molecular interaction networks are nowadays assembled in biomedical researches along with important technological advances. Diverse interaction measures, for which input solely consisting of the incidence of causal-factors, with the corresponding outcome of an inquired effect, are formulated without an obvious mathematical unity. Consequently, conceptual and practical ambivalences arise. We identify here a probabilistic requirement consistent with that input, and find, by the rules of probability theory, that it leads to a model multiplicative in the complement of the effect. Important practical properties are revealed along these theoretical derivations, that has not been noticed before.

Next Generation Winemakers: Genetic Engineering in Saccharomyces cerevisiae for Trendy Challenges

The most famous yeast of all, Saccharomyces cerevisiae, has been used by humankind for at least 8000 years, to produce bread, beer and wine, even without knowing about its existence. Only in the last century we have been fully aware of the amazing power of this yeast not only for ancient uses but also for biotechnology purposes. In the last decades, wine culture has become and more demanding all over the world. By applying as powerful a biotechnological tool as genetic engineering in S. cerevisiae, new horizons appear to develop fresh, improved, or modified wine characteristics, properties, flavors, fragrances or production processes, to fulfill an increasingly sophisticated market that moves around 31.4 billion € per year.

Advances in synthetic lethality for cancer therapy: cellular mechanism and clinical translation

Synthetic lethality is a lethal phenomenon in which the occurrence of a single genetic event is tolerable for cell survival, whereas the co-occurrence of multiple genetic events results in cell death. The main obstacle for synthetic lethality lies in the tumor biology heterogeneity and complexity, the inadequate understanding of synthetic lethal interactions, drug resistance, and the challenges regarding screening and clinical translation. Recently, DNA damage response inhibitors are being tested in various trials with promising results. This review will describe the current challenges, development, and opportunities for synthetic lethality in cancer therapy. The characterization of potential synthetic lethal interactions and novel technologies to develop a more effective targeted drug for cancer patients will be explored. Furthermore, this review will discuss the clinical development and drug resistance mechanisms of synthetic lethality in cancer therapy. The ultimate goal of this review is to guide clinicians at selecting patients that will receive the maximum benefits of DNA damage response inhibitors for cancer therapy.

Biomedical applications of yeasts - a patent view, part two: era of humanized yeasts and expanded applications

INTRODUCTION

Yeast humanization, ranging from a simple point mutation to substitution of yeast gene(s) or even a complete pathway by human counterparts has enormously expanded yeast biomedical applications.

AREAS COVERED

General and patent-oriented insights into the application of native and humanized yeasts for production of human glycoproteins (gps) and antibodies (Abs), toxicity/mutagenicity assays, treatments of gastrointestinal (GI) disorders and potential drug delivery as a probiotic (with emphasis on Saccharomyces bulardii) and studies on human diseases/cancers and screening effective drugs.

EXPERT OPINION

Humanized yeasts cover the classical advantageous features of a 'microbial eukaryote' together with advanced human cellular processes. These unique characteristics would permit their use in the production of functional and stable therapeutic gps and Abs in lower prices compared to mammalian (CHO) production-based systems. Availability of yeasts humanized for cytochrome P450 s will expand their application in metabolism-related chemical toxicity assays. Engineered S. bulardii for expression of human proteins might expand its application by synergistically combining the probiotic activity with the treatment of metabolic diseases such as phenylketonuria via GI-delivery. Yeast models of human diseases will facilitate rapid functional/phenotypic characterization of the disease-producing mutant genes and screening of the therapeutic compounds using yeast-based high-throughput research techniques (Yeast one/two hybrid systems) and viability assays.

How yeast cells deal with stalled replication forks

DNA polymerases sometimes stall during DNA replication at sites where DNA is damaged, or upon encounter with proteins or secondary structures of DNA. When that happens, the polymerase clamp PCNA can become modified with a single ubiquitin moiety at lysine 164, opening DNA Damage Tolerance (DDT) mechanisms that either repair or bypass the lesions. An alternative repair mechanism is the salvage recombination (SR) pathway, which copies information from the sister chromatid. SUMOylation of PCNA at the same lysine, or at lysine 127, can recruit the Srs2 helicase, which negatively controls SR. Recently, we have dissected the relationship between SR and the DDT pathways, and showed that overexpression of either the PCNA unloader Elg1, or the Rad52 homologous recombination protein, can bypass the repression by Srs2. Our results shed light on the interactions between different DNA damage repair/bypass proteins, and underscore the importance of PCNA modifications in organizing the complex task of dealing with DNA damage during replication of the genetic material.

Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants

Over the last 30 years, computational biologists have developed increasingly realistic mathematical models of the regulatory networks controlling the division of eukaryotic cells. These models capture data resulting from two complementary experimental approaches: low-throughput experiments aimed at extensively characterizing the functions of small numbers of genes, and large-scale genetic interaction screens that provide a systems-level perspective on the cell division process. The former is insufficient to capture the interconnectivity of the genetic control network, while the latter is fraught with irreproducibility issues. Here, we describe a hybrid approach in which the 630 genetic interactions between 36 cell-cycle genes are quantitatively estimated by high-throughput phenotyping with an unprecedented number of biological replicates. Using this approach, we identify a subset of high-confidence genetic interactions, which we use to refine a previously published mathematical model of the cell cycle. We also present a quantitative dataset of the growth rate of these mutants under six different media conditions in order to inform future cell cycle models.

CATS: Cas9-assisted tag switching. A high-throughput method for exchanging genomic peptide tags in yeast

BACKGROUND

The creation of arrays of yeast strains each encoding a different protein with constant tags is a powerful method for understanding how genes and their proteins control cell function. As genetic tools become more sophisticated there is a need to create custom libraries encoding proteins fused with specialised tags to query gene function. These include protein tags that enable a multitude of added functionality, such as conditional degradation, fluorescent labelling, relocalization or activation and also DNA and RNA tags that enable barcoding of genes or their mRNA products. Tools for making new libraries or modifying existing ones are becoming available, but are often limited by the number of strains they can be realistically applied to or by the need for a particular starting library.

RESULTS

We present a new recombination-based method, CATS - Cas9-Assisted Tag Switching, that switches tags in any existing library of yeast strains. This method employs the reprogrammable RNA guided nuclease, Cas9, to both introduce endogenous double strand breaks into the genome as well as liberating a linear DNA template molecule from a plasmid. It exploits the relatively high efficiency of homologous recombination in budding yeast compared with non-homologous end joining.

CONCLUSIONS

The method takes less than 2 weeks, is cost effective and can simultaneously introduce multiple genetic changes, thus providing a rapid, genome-wide approach to genetic modification.

The CRISPR toolbox in medical mycology: State of the art and perspectives

Fungal pathogens represent a major human threat affecting more than a billion people worldwide. Invasive infections are on the rise, which is of considerable concern because they are accompanied by an escalation of antifungal resistance. Deciphering the mechanisms underlying virulence traits and drug resistance strongly relies on genetic manipulation techniques such as generating mutant strains carrying specific mutations, or gene deletions. However, these processes have often been time-consuming and cumbersome in fungi due to a number of complications, depending on the species (e.g., diploid genomes, lack of a sexual cycle, low efficiency of transformation and/or homologous recombination, lack of cloning vectors, nonconventional codon usage, and paucity of dominant selectable markers). These issues are increasingly being addressed by applying clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 mediated genetic manipulation to medically relevant fungi. Here, we summarize the state of the art of CRISPR-Cas9 applications in four major human fungal pathogen lineages: Candida spp., Cryptococcus neoformans, Aspergillus fumigatus, and Mucorales. We highlight the different ways in which CRISPR has been customized to address the critical issues in different species, including different strategies to deliver the CRISPR-Cas9 elements, their transient or permanent expression, use of codon-optimized CAS9, and methods of marker recycling and scarless editing. Some approaches facilitate a more efficient use of homology-directed repair in fungi in which nonhomologous end joining is more commonly used to repair double-strand breaks (DSBs). Moreover, we highlight the most promising future perspectives, including gene drives, programmable base editors, and nonediting applications, some of which are currently available only in model fungi but may be adapted for future applications in pathogenic species. Finally, this review discusses how the further evolution of CRISPR technology will allow mycologists to tackle the multifaceted issue of fungal pathogenesis.

A new inducible CRISPR-Cas9 system useful for genome editing and study of double-strand break repair in Candida glabrata

In recent years, the CRISPR-Cas9 system has proven extremely useful for genome editing in many species, including the model yeast Saccharomyces cerevisiae and other yeast species such as Candida glabrata. Inducible CRISPR-Cas9 systems have the additional advantage of allowing to separate the transformation step of the organism by the CRISPR-Cas9 system, from the cutting and repair steps. This has indeed been developed in S. cerevisiae, where most inducible expression systems rely on the GAL promoters. Unfortunately, C. glabrata is gal- and lacks the GAL genes, like many other yeast species. We report here the use of a vector expressing cas9 under the control of the MET3 promoter, with the guide RNA cloned into the same plasmid. We show that it can be used efficiently in C. glabrata, for both described outcomes of CRISPR-Cas9-induced chromosome breaks; nonhomologous end joining in the absence of a homologous repair template; and homologous recombination in the presence of such a template. This system therefore allows easy editing of the genome of C. glabrata, and its inducibility may allow identification of essential genes in this asexual yeast, where spore lethality cannot be observed, as well as the study of double-strand break repair.

Evolutionary engineering and molecular characterization of a caffeine-resistant Saccharomyces cerevisiae strain

Caffeine is a naturally occurring alkaloid, where its major consumption occurs with beverages such as coffee, soft drinks and tea. Despite a variety of reports on the effects of caffeine on diverse organisms including yeast, the complex molecular basis of caffeine resistance and response has yet to be understood. In this study, a caffeine-hyperresistant and genetically stable Saccharomyces cerevisiae mutant was obtained for the first time by evolutionary engineering, using batch selection in the presence of gradually increased caffeine stress levels and without any mutagenesis of the initial population prior to selection. The selected mutant could resist up to 50 mM caffeine, a level, to our knowledge, that has not been reported for S. cerevisiae so far. The mutant was also resistant to the cell wall-damaging agent lyticase, and it showed cross-resistance against various compounds such as rapamycin, antimycin, coniferyl aldehyde and cycloheximide. Comparative transcriptomic analysis results revealed that the genes involved in the energy conservation and production pathways, and pleiotropic drug resistance were overexpressed. Whole genome re-sequencing identified single nucleotide polymorphisms in only three genes of the caffeine-hyperresistant mutant; PDR1, PDR5 and RIM8, which may play a potential role in caffeine-hyperresistance.